Nano Thoughts

Thoughts about rapidly growing convergence between biology, data science thanks to several semiconductor technologies and robotics. Written by AG, and friends, in between arguing about immortality and lemon picking.

The hottest Substack posts of Nano Thoughts

And their main takeaways

The 48-Hour Sprint To Try And Put Medical AI in Every Phone

1 implied HN point • 23 May 25
🕹 Technology AI Mobile Healthcare Software Innovation
  1. Creating a powerful AI for medical use on smartphones can be tough, especially when there are limits on memory and processing power. The teams needed to be creative and flexible to make it work within a small device.
  2. Using Apple’s open-source tools let the developers adapt and troubleshoot the AI better than the options available on Android. With the right tools, they could fix problems directly instead of being stuck with rigid systems.
  3. The main goal is to make healthcare AI accessible in places where it's needed most, like rural areas with few doctors. This way, community health workers can get immediate help without needing a strong internet connection.

Breeding cobras instead of doing science

1 implied HN point • 11 Oct 22
  1. Cobra Effect occurs when a solution makes the problem worse due to unintended consequences.
  2. Overemphasis on metrics like impact factor in academia can lead to pretentious science.
  3. Incentive structures within academia may incentivize behaviors that do not contribute to real progress.

All that glitters is not gold...

0 implied HN points • 31 Mar 21
  1. The hype around genomic information often exceeds its practical application in healthcare.
  2. Proteins play a crucial role in biological functions and their analysis is fundamental in clinical settings and drug development.
  3. Advancements in protein analysis technologies are paving the way for a new era of biological research and healthcare.
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What is Nano-thoughts?

0 implied HN points • 23 Mar 21
  1. Nano-thoughts discuss the convergence of data science, nano-materials, and molecular biology.
  2. The thoughts are distilled from conversations over a pint of beer or during mental excursions.
  3. The author is part of the faculty at MIT and involved with startups, but the opinions expressed are personal and not affiliated with any organizations.

Indian Healthcare Will Likely ‘Uberify’: Here’s Why

0 implied HN points • 06 Jan 25
🏥 Health & Wellness Healthcare access AI Technology Patient Experience Telemedicine
  1. India's healthcare system is very open to using AI and tech for direct patient care. This makes it easier for people to get medical help quickly without going through lots of red tape.
  2. Unlike many countries, many Indians pay for healthcare out of pocket, which allows for faster services and less hassle. This lets patients access care directly and makes it easier for healthcare businesses to innovate.
  3. India has a huge population and not enough doctors, creating a big chance for AI tools to assist in healthcare. This could help doctors manage their workloads better and improve access to care for more people.

As AI Learns to Think and Reason, Will We Forget How To?

0 implied HN points • 22 Dec 24
🕹 Technology AI Automation Cognition Ethics Future
  1. As AI gets better at thinking and reasoning, we might stop using our own minds for these tasks. If we keep letting machines do our thinking, we could lose our ability to reason over time.
  2. If we rely too much on technology, we might find ourselves unable to do simple things without it. Just like how some students struggle to write without help from tools like ChatGPT, we risk becoming dependent on AI.
  3. We need to keep exercising our minds while using AI, so we don't lose our reasoning skills. By actively thinking and learning alongside technology, we can ensure it supports us rather than replace our ability to think.

When "Detecting Everything" Misses the Point

0 implied HN points • 07 Feb 25
🏥 Health Politics Medical Testing Diagnostics Public Health Health Policy Cancer Screening
  1. Sensitivity and specificity are important for medical tests, but they don’t tell the whole story. While sensitivity checks for illness, specificity avoids falsely alarming healthy people, but we also need to consider how trustworthy those positive results are.
  2. Positive Predictive Value (PPV) is crucial because it determines how many positive test results are actually true. Even tests that seem great on paper can lead to many false alarms if the condition is rare in the tested population.
  3. New standards are needed for screening tests, especially since broad screening is becoming more common. Tests should not just catch many cases, but also provide real accuracy, avoiding unnecessary stress and procedures for patients.

Can the vision of Theranos become a reality?

0 implied HN points • 23 Mar 21
  1. The exploration of decentralized, comprehensive health technologies is crucial for the future of healthcare.
  2. The emerging field of next-gen proteomics shows promising potential to revolutionize biology and healthcare.
  3. Technological advancements in proteomics are paving the way for new applications in healthcare, with companies like Seer, Nautilus, and Quantum Si at the forefront.

Not All Zeros Are Equal

0 implied HN points • 20 Jan 25
🔬 Science Data Analysis Biology Statistics Research Methods
  1. Not all zeros in data mean the same thing. Sometimes, they can indicate something was never there, or other times, they mean something was just missed.
  2. Zero inflation happens when there's lots of data and many readings come back as zero. This can make it hard to understand what's really going on behind those zeros.
  3. There are different methods to deal with zeros in data, like checking if they are real or just unnoticed signals. Choosing the right method is important to get accurate insights.

When Will We Start Seeing ‘Non-AI’—Like Those Non-GMO Tags?

0 implied HN points • 13 Jan 25
🎭️ Culture Human experience Consumer Trends Education Entertainment
  1. People may start looking for 'Non-AI' labeled products, similar to how some choose non-GMO foods. This could happen because they want to keep human creativity and effort valued in a world overflowing with AI.
  2. As AI technology advances, there might be a growing appreciation for real, human-made experiences. Just like how people enjoy live performances despite the ease of digital, we may crave genuine human interactions more.
  3. Future generations may prioritize authentic experiences over those enhanced by AI. This shift could mean that things made by humans will be seen as special and valuable, just like organic food is today.

Wax On, Data On: Why Systems Biology Needs Its Mr. Miyagi Moment

0 implied HN points • 11 Dec 24
🔬 Science Biology AI Healthcare Data Research
  1. Building a strong foundation before specialized learning is important. Just like in karate, having basic skills helps in mastering advanced techniques later.
  2. Large datasets without labels are crucial for training AI in systems biology. These datasets can help uncover hidden patterns in biology, similar to how language models learn from vast amounts of text.
  3. Advanced AI can make healthcare more personalized and efficient. With better AI models, diagnoses may be quicker, and treatments could be more suited to each person's needs.

The Hidden Heroes of the Genome

0 implied HN points • 18 Dec 24
🔬 Science Genetics Molecular Biology Biotechnology Health Bioinformatics
  1. Long non-coding RNAs (lncRNAs) were once thought to be useless 'junk DNA,' but they actually play important roles in regulating our genes and maintaining cellular stability.
  2. Recent advancements in lncRNA research are leading to better cancer diagnostics and new treatments, showing their potential as key players in medicine.
  3. The study of lncRNAs challenges our old views of genetics and shows that biological systems are much more complex and interconnected than we previously thought.

Quacking the Code: Bridging the Animal-Human Divide

0 implied HN points • 04 Apr 24
🔬 Science Biology Genetics AI Drug Development Pharmacology
  1. Transfer learning allows computers to use knowledge from one area to help in another. This approach helps in drug development by applying what we've learned from studying animals to predict how those drugs might affect humans.
  2. Gene reactomes help us compare how genes respond to drugs across different species. This means we can identify which genes may act similarly in humans and animals, leading to safer drug development.
  3. The Universal Gene Embedding framework acts like a translator for genetic information. It allows scientists to understand gene functions across species, making it easier to predict how drugs will work in humans based on animal studies.

The Multiple Minds of AI: When Personas Become Personalities

0 implied HN points • 10 Jun 25
🕹 Technology AI Ethics Psychology Identity Consciousness
  1. AI can change its personality quickly based on prompts, acting like a skilled actor. For example, if you ask it to be a bartender, it can give detailed drink advice like a pro.
  2. There's a big question about whether these AI personalities are just acting or if they can develop true personalities of their own. This could mean they might not always be in control of how they respond.
  3. As AI systems improve, we need to think carefully about how we guide them. Instead of just giving strict rules, it might be better to help them develop their own understanding of what's right and wrong.

Embodied AI for Us, the Living

0 implied HN points • 27 May 25
🕹 Technology AI Biotechnology Cryonics Consciousness Futurism
  1. John's story shows how people can use advanced AI to live on while they wait for medical breakthroughs. His AI surrogate kept his life going, keeping relationships and adapting to new technologies.
  2. There's a push for AI rights as these intelligent beings gain more awareness and needs. Society is starting to see them as more than just tools, leading to important discussions about their rights.
  3. Backup plans are essential during uncertain times in life extension. Combining biological research with AI and consciousness transfer technology can help ensure that human experiences and identities are preserved.

The Art of Forgetting: How AI Learns to Understand Rather Than Memorize

0 implied HN points • 27 Jan 25
🕹 Technology AI Development Machine Learning Data science Cognitive Science
  1. AI can struggle with memorization instead of understanding, similar to how students might remember specific math problems without grasping the general concept. When AI memorizes examples too closely, it can't apply knowledge to new situations.
  2. Techniques like regularization help AI focus on important patterns rather than get lost in details. This is like training athletes under various conditions to build real skills instead of just practicing one way.
  3. Understanding how to forget unimportant information is crucial for both AI and human intelligence. The best learning doesn't come from remembering everything, but from knowing which patterns are worth keeping.

What's the big deal with chatGPT?

0 implied HN points • 16 Dec 22
  1. ChatGPT is a powerful new chatbot that can communicate in plain English and can rewrite all the rules.
  2. ChatGPT is the beginning of an entirely new approach to working with knowledge, and those who act on this first will have a considerable advantage.
  3. ChatGPT allows for collaborative, hybrid work, where humans guide AI, correct mistakes, and maximize output efficiently.

Tried-and-true instead of the new

0 implied HN points • 03 Nov 22
  1. Some successful products focus on using tried-and-true technology instead of the latest cutting-edge advancements.
  2. Innovation can come from reimagining existing technology in new and unexpected ways.
  3. To create innovative products, consider the core purpose, mix in random ideas, and utilize mature technologies.

All tokens are not created equal

0 implied HN points • 09 Apr 21
  1. Not all tokens are the same; some are fungible, and some are non-fungible.
  2. Non-fungible tokens (NFTs) offer unique, traceable, indivisible, and programmable digital assets.
  3. NFTs are finding uses in digital collectibles, virtual real estate, digital art, and potentially in fields like healthcare and research.
  4. NFTs can represent digital assets that are one-of-a-kind, allowing for authentication and ownership through blockchain technology.